Video human behavior recognition method based on significant trajectory and time-space evolution information

A recognition method and remarkable technology, applied in the field of computer vision, can solve the problem of ignoring middle and high-level semantic information, and achieve the effect of improving the recognition effect

Active Publication Date: 2017-03-22
SUN YAT SEN UNIV
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Problems solved by technology

In addition, representation methods based on low-level visual features have achieved good results in human behavior recognition...

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  • Video human behavior recognition method based on significant trajectory and time-space evolution information
  • Video human behavior recognition method based on significant trajectory and time-space evolution information
  • Video human behavior recognition method based on significant trajectory and time-space evolution information

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Embodiment 1

[0053] like figure 1As shown, the video human behavior recognition method based on salient trajectories and spatio-temporal evolution information of the present invention first extracts dense trajectories on the basis of improving dense trajectories, and defines the saliency of frames and trajectories through saliency detection; secondly, removes background trajectories through adaptive screening , to obtain the salient foreground trajectory; then use the Gaussian mixture model and Fisher vector to obtain the video frame representation, that is, the trajectory bundle; use the big data linear classifier to mine the temporal structure information between the trajectory bundles as the video representation, and finally perform feature training and identify.

[0054] like figure 1 , figure 2 As shown, in the step of extracting the foreground motion trajectory based on salient trajectory features, the longest continuous frame number L of the trajectory length is set to 15, the co...

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Abstract

The present invention provides a video human behavior recognition method based on a significant trajectory and time-space evolution information. According to the method, the optical flow information in a video is fully utilized, on the basis of improving a dense trajectory, through defining the static significance and dynamic significance of the trajectory, with a linear fusion mode, the combined significance of the trajectory is obtained through calculation, thus a background movement trajectory is effectively removed, and a foreground movement trajectory is extracted. For a problem that the rich middle and high level semantic information in a behavior video is ignored by a traditional representation method based on a low-level visual characteristic, the invention provides middle level visual characteristic expression which is a trajectory beam, human body behavior time-space evolution information is extracted to be a video characteristic expression, the background trajectory is removed effectively, the foreground movement trajectory is extracted, and the recognition effect of an algorithm is improved significantly.

Description

technical field [0001] The invention relates to the technical field of computer vision, and more specifically, to a video human behavior recognition method based on salient trajectory and spatio-temporal evolution information. Background technique [0002] With the development of the Internet and multimedia, video has become the main way for people to obtain information. Video-based human behavior recognition technology has been widely used in a series of scenarios such as intelligent video surveillance, video retrieval, virtual reality, and human interaction. In recent years, a large number of human behavior recognition methods from surveillance scenes to natural scenes have emerged, and the recognition accuracy of various public data sets is also constantly improving. However, the complexity of video motion in natural scenes (such as camera motion) leads to serious optical flow deviation, the inaccurate human positioning algorithm leads to mixed foreground and background m...

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Application Information

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IPC IPC(8): G06K9/00
CPCG06V40/10G06V20/41
Inventor 衣杨程阳许楚萍兰天翔王昭
Owner SUN YAT SEN UNIV
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